Validation and demonstration of a new comprehensive model of Alzheimer's disease progression

Yaakov Stern, Eric Stallard, Bruce Kinosian, Carolyn Zhu, Stephanie Cosentino, Zhezhen Jin, Yian Gu

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Introduction: Identifying the course of Alzheimer's disease (AD) for individual patients is important for numerous clinical applications. Ideally, prognostic models should provide information about a range of clinical features across the entire disease process. Previously, we published a new comprehensive longitudinal model of AD progression with inputs/outputs covering 11 interconnected clinical measurement domains. Methods: Here, we (1) validate the model on an independent cohort; and (2) demonstrate the model's utility in clinical applications by projecting changes in 6 of the 11 domains. Results: Survival and prevalence curves for two representative outcomes—mortality and dependency—generated by the model accurately reproduced the observed curves both overall and for patients subdivided according to risk levels using an independent Cox model. Discussion: The new model, validated here, effectively reproduces the observed course of AD from an initial visit assessment, allowing users to project coordinated developments for individual patients of multiple disease features.

Original languageEnglish
Pages (from-to)1698-1708
Number of pages11
JournalAlzheimer's and Dementia
Issue number10
StatePublished - Oct 2021


  • clinical signs/symptoms
  • dementia progression
  • grade of membership
  • heterogeneity
  • longitudinal follow-up
  • prognosis


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